mirror of
https://github.com/BigBodyCobain/Shadowbroker.git
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BigBodyCobain
b7824004db
Cherry-picked from @Bobpick PR #391 (GT + OpenClaw slice): Bayesian strategic-risk engine, map overlay, OpenClaw commands, and telegram_rhetoric watchdog. Off by default (GT_ANALYTICS_ENABLED=false, gt_risk layer false). 1 vCPU nodes get cgroup detection, UI warning on layer toggle, and lean profile that skips scheduled ingest/Louvain unless GT_ANALYTICS_ACK_LOW_CPU=true. Backtest HUD removed from dashboard (OpenClaw/API regression only). Co-authored-by: Robert Pickett <bobpickettsr@yahoo.com> Co-authored-by: Cursor <cursoragent@cursor.com>
107 lines
3.3 KiB
Python
107 lines
3.3 KiB
Python
"""Container-aware runtime limits for fleet vs desktop deployments."""
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from __future__ import annotations
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import os
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from functools import lru_cache
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from pathlib import Path
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from typing import Any
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def _read_first_int(path: Path) -> int | None:
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try:
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raw = path.read_text(encoding="utf-8").strip().split()[0]
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return int(raw)
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except (OSError, ValueError, IndexError):
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return None
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def detect_cpu_limit() -> float | None:
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"""Effective CPU cores from cgroup quota (Docker ``cpus:``), else host count."""
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cgroup_v2 = Path("/sys/fs/cgroup/cpu.max")
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if cgroup_v2.is_file():
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try:
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parts = cgroup_v2.read_text(encoding="utf-8").strip().split()
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if len(parts) >= 2 and parts[0] != "max":
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quota = int(parts[0])
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period = int(parts[1])
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if quota > 0 and period > 0:
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return round(quota / period, 3)
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except (OSError, ValueError):
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pass
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cgroup_v1_quota = Path("/sys/fs/cgroup/cpu/cpu.cfs_quota_us")
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cgroup_v1_period = Path("/sys/fs/cgroup/cpu/cpu.cfs_period_us")
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if cgroup_v1_quota.is_file() and cgroup_v1_period.is_file():
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quota = _read_first_int(cgroup_v1_quota)
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period = _read_first_int(cgroup_v1_period)
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if quota is not None and period and quota > 0:
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return round(quota / period, 3)
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try:
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import os as _os
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count = _os.cpu_count()
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return float(count) if count else None
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except Exception:
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return None
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def detect_memory_limit_mb() -> int | None:
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cgroup_v2 = Path("/sys/fs/cgroup/memory.max")
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if cgroup_v2.is_file():
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try:
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raw = cgroup_v2.read_text(encoding="utf-8").strip()
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if raw and raw != "max":
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return int(int(raw) / (1024 * 1024))
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except (OSError, ValueError):
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pass
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cgroup_v1 = Path("/sys/fs/cgroup/memory/memory.limit_in_bytes")
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if cgroup_v1.is_file():
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try:
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raw = _read_first_int(cgroup_v1)
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if raw is not None and raw < (1 << 62):
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return int(raw / (1024 * 1024))
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except (OSError, ValueError):
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pass
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return None
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def resolve_profile_name() -> str:
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explicit = str(os.environ.get("GT_ANALYTICS_PROFILE", "")).strip().lower()
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if explicit in {"lean", "standard"}:
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return explicit
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cpu = detect_cpu_limit()
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if cpu is not None and cpu <= 1.0:
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return "lean"
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return "standard"
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@lru_cache(maxsize=1)
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def get_runtime_profile() -> dict[str, Any]:
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cpu_limit = detect_cpu_limit()
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memory_mb = detect_memory_limit_mb()
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profile = resolve_profile_name()
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lean = profile == "lean"
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return {
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"profile": profile,
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"cpu_limit": cpu_limit,
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"memory_limit_mb": memory_mb,
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"gt_analytics": {
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"recommended": not lean,
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"lean_node": lean,
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"warning": (
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"This node is capped at 1 vCPU. Enabling Strategic Risk (Derived OSINT) "
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"may slow Telegram, GDELT, and other OSINT fetches. Set "
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"GT_ANALYTICS_ACK_LOW_CPU=true after enabling GT_ANALYTICS_ENABLED to run "
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"the full engine on lean hardware."
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if lean
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else None
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),
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},
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}
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def clear_runtime_profile_cache() -> None:
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get_runtime_profile.cache_clear()
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